Hyper-heuristics is a fairly recent technique that aims at effectively solving various real-world
optimization problems. This is the first book on hyper-heuristics, and aims to bring together …

A large class of entity extraction tasks from text that is either semistructured or fully
unstructured may be addressed by regular expressions, because in many practical cases …

Data mining requires a pre-processing task in which the data are prepared and cleaned for
ensuring the quality. Missing value occurs when no data value is stored for a variable in an …

Explainability is essential for users to effectively understand, trust, and manage powerful
artificial intelligence solutions. Decision trees are one of the pioneer explanaible artificial …

The fields of machine meta-learning and hyper-heuristic optimisation have developed
mostly independently of each other, although evolutionary algorithms (particularly genetic …

Cyber security in the context of big data is known to be a critical problem and presents a
great challenge to the research community. Machine learning algorithms have been …

Decision-tree induction algorithms are widely used in machine learning applications in
which the goal is to extract knowledge from data and present it in a graphically intuitive way …

Bridge deterioration is inevitable in service, and the inspection and maintenance of bridges
are needed to ensure structural integrity. To make cost-effective inspection plans, bridge …

We consider the automatic synthesis of an entity extractor, in the form of a regular
expression, from examples of the desired extractions in an unstructured text stream. This is a …

In the context of big data, many scientific communities aim to provide efficient approaches to
accommodate large-scale datasets. This is the case of the machine-learning community …